TY - GEN
T1 - A DESIGN FRAMEWORK FOR EVOLVING CYBER-PHYSICAL-SOCIAL SYSTEM (CPSS) BASED ON FORCE FIELD
AU - Zhou, Ziqing
AU - Sun, Yanwei
AU - Ouyang, Chun
AU - Gan, Zhongxue
AU - Ming, Zhenjun
N1 - Publisher Copyright:
Copyright © 2022 by ASME.
PY - 2022
Y1 - 2022
N2 - A Cyber-Physical-Social System (CPSS), as an extension of cyber-physical system (CPS), has received considerable attention in recent years both in academia and industry. Compared to CPS, CPSS has great advantages on efficiency, adaption and robustness due to the existence of self-organizing social system. One of the difficulties in the design of CPSS is anchored in the lack of a control mechanism to achieve self-organizing capability while the system is evolving. To address this problem, we propose a design framework for evolving CPSS based on the force field, which is composed of inner force and task force field. In addition to the framework, we present several performance evaluation indicators to quantify the self-organizing capability of the system, including consumption, emergence, and scalability. We test the performance of the framework using a disaster-relief example, which involves the computational control algorithm (cyber system), robot (physical system), and self-organizing swarm (social system). The result shows that based on our framework, the system can automatically evolve from disorder to order, adapt to the changeable environment and successfully finish the task in a very efficient manner.
AB - A Cyber-Physical-Social System (CPSS), as an extension of cyber-physical system (CPS), has received considerable attention in recent years both in academia and industry. Compared to CPS, CPSS has great advantages on efficiency, adaption and robustness due to the existence of self-organizing social system. One of the difficulties in the design of CPSS is anchored in the lack of a control mechanism to achieve self-organizing capability while the system is evolving. To address this problem, we propose a design framework for evolving CPSS based on the force field, which is composed of inner force and task force field. In addition to the framework, we present several performance evaluation indicators to quantify the self-organizing capability of the system, including consumption, emergence, and scalability. We test the performance of the framework using a disaster-relief example, which involves the computational control algorithm (cyber system), robot (physical system), and self-organizing swarm (social system). The result shows that based on our framework, the system can automatically evolve from disorder to order, adapt to the changeable environment and successfully finish the task in a very efficient manner.
UR - http://www.scopus.com/inward/record.url?scp=85142468534&partnerID=8YFLogxK
U2 - 10.1115/DETC2022-89892
DO - 10.1115/DETC2022-89892
M3 - Conference contribution
AN - SCOPUS:85142468534
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 48th Design Automation Conference (DAC)
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2022
Y2 - 14 August 2022 through 17 August 2022
ER -